The invention relates to methods of optimizing operating parameters of analytical instruments, and in particular to systems and methods using simplex algorithms for optimizing operating parameters of mass spectrometers.
Mass spectrometers typically include multiple ion lenses and guides disposed between an ion source and an analyzer. In a common design, charged liquid droplets are generated in an ionization chamber using an atmospheric pressure ionization method such as electrospray ionization (ESI) or atmospheric pressure chemical ionization (APCI). The droplets are desolvated, and pass into a vacuum chamber through an orifice that limits the gas flow into the chamber. The ions are guided through one or more electrodynamic ion guiding structures and apertures into a mass analyzer. The signal quality of a mass spectrometer generally depends on multiple spectrometer operating parameters, such as a set of voltages applied to lensing elements positioned between the ion source and analyzer.
Several approaches have been proposed for optimizing instrument parameters such as lens voltages. In a common approach, each parameter is optimized sequentially. For example, measurements are performed for a range of first lens voltages while all other voltages are kept fixed, until a local maximum of the first voltage is found. The process is then repeated for the other lenses, and again for the whole set of lenses. Such an approach may require a relatively high number of measurements to locate an optimal parameter set.
Another optimization approach is based on the simplex family of algorithms (for simplicity, referred to hereinafter as the simplex algorithm). For a two-dimensional parameter space, the simplex algorithm has been described as a triangle flipping its way up a mountainside to find the top of the mountain. In this example, the x- and y-coordinates denote instrument parameters, while the mountain height represents the instrument figure-of-merit to be optimized. The algorithm discards the worst (lowest) point of the triangle, chooses a new point, for example by reflecting the old point with respect to the remaining two, and repeats the process until the top is found. The triangle or its equivalent in multi-dimensional space is commonly called a simplex.
References describing parameter optimization methods for mass spectrometers include Elling et al, “Computer-Controlled Simplex Optimization on a Fourier Transform Ion Cyclotron Resonance Mass Spectrometer,” Anal. Chem. 61:330-334 (1989), Mas et al., “99Tc Atom Counting by Quadrupole ICP-MS. Optimisation of the instrumental response,” Nuclear Instruments & Methods in Physics Research, A484:660-667 (2002), Evans et al., “Optimization Strategies for the Reduction of Non-Spectroscopic Interferences in Inductively Coupled Plasma Mass Spectrometry,” Spectrochimica Acta, 47B(8): 1001-1012 (1992), Vertes et al., “Non-Linear Optimization of Cylindrical Electrostatic Lenses,” International Journal of Mass Spectrometry and Ion Processes, 84:255-269 (1988), and Ford et al., “Simplex Optimization of the Plasma Parameters and Ion Optics of an Inductively Coupled Mass Spectrometer with Pure Argon and Doped Argon Plasmas, using a Multi-Element Figure of Merit,” Analytica Chimica Acta, 285:23-31 (1994).
Optimizing mass spectrometer parameters may be particularly difficult in the presence of noise and instrument drift, which may significantly affect instrument performance.